Social movements and human rights rhetoric in tobacco

In this paper, we analyze a performance model for the TCP Congestion Avoidance algorithm. The model predicts the bandwidth of a sustained TCP connection subjected to light to moderate packet losses, such as loss caused by network congestion. It assumes that TCP avoids retransmission timeouts

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Vegas is a new implementation of TCP that achieves between 40 and 70 % better throughput, with one-fifth to onehalf the losses, as compared to the implementation of TCP in the Reno distributionof BSD Unix. This paper motivates and describes the three key techniques employed by Vegas, and presents the results of a comprehensive experimental performance study—using both simulations and measurements on the Internet—of the Vegas and Reno implementations of TCP. 1

A new real-time obstacle avoidance method for mobile robots has been developed and implemented. This method, named the vector field histogram(VFH), permits the detection of unknown obstacles and avoids collisions while simultaneously steering the mobile robot toward the target. The VFH method uses

between robots R1 and R2 in the situation depicted in Figure 1(a), but also that in Figure 1(b), which is typically not considered as a collision in existing multi-robot systems. (a) (b) (c) Figure 2: Illustration of deadloop. The green square and the red square are the robot positions and the goal

People approach pleasure and avoid pain. To discover the true nature of approach-avoidance motivation, psychologists need to move beyond this hedonic principle to the principles that underlie the different ways that it operates. One such principle is regulatory focus, which distinguishes self

A shared data structure is lock-free if its operations do not require mutual exclusion. If one process is interrupted in the middle of an operation, other processes will not be prevented from operating on that object. In highly concurrent systems, lock-free data structures avoid common problems

In this paper, a new probabilistic tagging method is presented which avoids problems that Markov Model based taggers face, when they have to estimate transition probabilities from sparse data. In this tagging method, transition probabilities are estimated using a decision tree. Based on this method

limitations of both long global wires and short local wires and discuss architectural design techniques that help us avoid the limitations of scaled wires.